Groundwater metal elements pollution is one of the most serious environmental problems in the tailings area. Identifying its distribution characteristics and sources provides data and methodological support for precise prevention and control of groundwater pollution. Spatial distribution characteristics of nine metal elements （Al， Zn， Cu， Mn， Pb， Cd， Fe， Ba， and As） in groundwater were revealed using descriptive statistics and kriging interpolation. A comprehensive evaluation of groundwater quality was conducted using a random forest model. Combined with correlation analysis， principal component analysis-multiple linear regression model， and Monte Carlo simulation， the sources of metal element pollution were quantitatively analyzed， and health risks were assessed for specific sources. The results showed that： ① In some areas， the levels of Al， Mn， Pb， Fe， Ba， and As in groundwater exceeded the Class III standards of the Groundwater Quality Standards. The exceedance rates from highest to lowest were： Mn （60.94%） = Fe （60.94%） > Al （46.88%） > As （6.25%） > Pb （4.69%） > Ba （3.13%）. ② Evaluation using the random forest model indicated that groundwater quality in the study area mainly fell within Classes II to IV， reflecting generally poor water quality. Key indicators affecting groundwater quality levels were Al， Pb， Fe， and Mn， with higher concentrations observed in the central > southern > northern parts. ③ The primary sources of groundwater metal element pollution included geological background， industrial activities， agricultural activities， traffic emissions， and tailings slag. Among these sources， tailings slag contributed the most （37%） to the accumulation of metal elements in groundwater. ④ Monte Carlo simulation results highlighted carcinogenic health risks for adults and both carcinogenic and non-carcinogenic risks for children due to groundwater metal elements. ⑤ Tailings slag was identified as the main contributor to carcinogenic risks （38.5%）， with Cd being the major contributor. On the other hand， geological background and industrial activities were the primary contributors to non-carcinogenic risks （40.6%）， primarily due to Al， Mn， and As. Therefore， significant attention is required to address groundwater environmental pollution issues in tailings areas.
Keywords: groundwater; health risks; metal elements; random forest model; source analysis.